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Sensitivity of hilbert magnitude and phase to structural damage

Sensitivity of hilbert magnitude and phase to structural dam...

引用

Smart Structures and Materials 2003 Conference

作者： Pines, D Salvino, L Univ Maryland Alfred Gessow Rotorcraft Ctr Smart Struct Lab College Pk MD 20742 USA

ISBN: (纸本)0819448613

This paper discusses a new signal-processing tool involving the use of empirical mode decomposition and its application to health monitoring of structures. Empirical mode decomposition is a time series analysis method that extracts a custom set of basis sets to describe the vibratory response of a system. In conjunction with the Hilbert Transform, the empirical mode decomposition method provides some unique information about the nature of the vibratory response. In this paper, the Hilbert phase for discrete one-dimensional structural elements is compared to the phase obtained from the use of dereverberated wave mechanics. Simulation results indicate that the Hilbert phase is proportional to mass and stiffness properties between two successive degrees of freedom. Hence, the Hilbert phase can be used to infer, locate and possibly quantify the amount of damage in a structure.

关键词： Diagnostics Wave propagation Sensors Signal analyzers Time series analysis Wave mechanics Aerospace engineering algorithm development Environmental sensing Smart structures

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ANOMALY DETECTION IN DATA USING NEURAL NETWORKS WITH NATURAL-SELECTION

ANOMALY DETECTION IN DATA USING NEURAL NETWORKS WITH NATURAL...

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1ST CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS

作者： DESSERT, PE Carnegie Group Inc. (United States)

ISBN: (纸本)0819408751

Frequently, time series data taken off machines contains erroneous data points due to errors in the measurement of the data. One such instance of measuring devices recording anomalies occurs in the `crash testing' of vehicles. In this task, senors are placed on the vehicle and the `crash dummy' and the vehicle is then crashed into a barrier. Force and acceleration data is collected which an engineer inspects for anomalies, correcting those that are found. Artificial neural network (ANN) technology was successfully applied to this problem to eliminate the cost and delay of this manual process. To apply ANN technology in this domain, two technical problems needed to be resolved; the appropriate network architecture and the size of the input set. These two issues are quite common and must be addressed in the development of any neural network application. To resolve both issues, I employed a machine learning algorithm that simulates the Darwinian concept of `survival of the fittest' known as the genetic learning algorithm (GLA). By combining the strength of the GLA and ANNs, a network architecture was created that `optimized' the size, speed, and accuracy of the ANN. This `hybridized' system also used the GLA to determine the `smallest' number of inputs into the ANN that were necessary to detect anomalies in data. This algorithm is known as GENENET, and is described in this paper.

关键词： Neural networks Genetics Neurons Artificial neural networks Network architectures Genetic algorithms Evolutionary algorithms algorithm development Sensors Measurement devices

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Phase coherence theory for data-mining and analysis: Application studies in spectroscopy

Phase coherence theory for data-mining and analysis: Applica...

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Opto-Ireland 2005 Conference

作者： Doyle, G McMillan, ND Murtagh, F O'Neill, M Riedel, S Perova, TS Unnikrishnan, S Moore, RA Inst Technol Carlow Carlow Ireland

ISBN: (纸本)0819458082

The paper investigates from the perspective of computer science the phase coherence theory (PCT) and phase coherent data-scatter (PCD-S). These techniques were originally developed for the area of optical tensiographic data mining and analysis but have a more general application in data mining. These developments have recently been augmented with the engineering of a software toolkit called TraceMiner. Although the toolkit was originally devised for tensiography it was developed to perform as a generic data mining and analysis application with PCT, PCD-S and a range of other data mining algorithms implemented. To date the toolkit has been utilised in its main application area, tensiography, but has also been applied to UV-visible spectroscopy. This work presents a critical investigation of the general utility of PCT, PCD-S and the toolkit for data mining and analysis. A new application of PCT and the TraceMiner software toolkit to Raman spectroscopy is presented with discussion of the relevant measures and the information provided by the toolkit. This provides more insight into the generic potential of the techniques for data mining. The analysis performed on theoretical Raman data is augmented with a study of experimental Raman data. Raman spectroscopy is used for composition and fault detection analysis in semiconductor surfaces. Finally, the utility of the PCT technique in comparison with traditional Raman spectroscopy methods is considered together with some more general applications in the field of imaging and machine vision.

关键词： Raman spectroscopy Data mining Data modeling Visualization Spectroscopy Statistical analysis Computer science Semiconductors algorithm development Software development

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Wavelet-cellular neural network architecture and learning algorithm

Wavelet-cellular neural network architecture and learning al...

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Conference on Independent Component Analyses, Wavelets, Unsupervised Smart Sensors and Neural Networks II

作者： Bal, A Ucan, ON Pastaci, H Alam, M Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

ISBN: (纸本)0819453625

Cellular Neural Networks (CNN) provides fast parallel computational capability for image processing applications. The behavior of the CNN is defined by two template matrices. In this paper, adjustment of these template-matrix coefficients have been realized using supervised learning algorithm based on back-propagation technique and wavelet function. Back-propagation algorithm has been modified for dynamic behavior of CNN. Wavelet function is utilized to provide the activation function derivation in this learning algorithm. The supervised learning algorithm is then executed to obtain a compact CNN architecture, called as Wave-CNN. The proposed new learning algorithm and Wave-CNN architecture performance have been tested for 2D image processing applications.

关键词： Neural networks Evolutionary algorithms Image processing Machine learning Wavelets algorithm development Matrices

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Bit-allocation considering mean absolute error for image compression

Bit-allocation considering mean absolute error for image com...

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Conference on Visual Information Processing IX

作者： Goswami, H Kozaitis, SP Florida Inst Technol Div Elect & Comp Sci & Engn Melbourne FL 32901 USA

ISBN: (纸本)0819436674

In lossy image compression schemes, often some distortion measure is minimized to arrive at a desired target bit rate. The distortion measure that has been most studied is the mean-squared-error (MSE). However, perceptual quality often does not agree with the notion of minimization of mean square error1 . Since MSE can not guarantee the optimality of perceptual quality, others error measures have been investigated. Others have found strong mathematical and practical perspective to choose a different error measure other than MSE, especially for image compression2. In Ref. 2 it is argued that the mean absolute error (MAE) measure is a better error measure than MSE for image compression from a perceptual standpoint. In addition, the MSE measure fails when only a small proportion of extreme observations is present3. In this paper we develop a bit allocation algorithm to minimize the MAE rather than MSE

关键词： Image compression Distortion Quantization algorithm development Wavelets Computer engineering Computer science Error analysis Quality measurement Visual information processing

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FAST VARIATIONAL algorithm FOR CLUTTER REMOVAL THROUGH PYRAMIDAL DOMAIN DECOMPOSITION

FAST VARIATIONAL ALGORITHM FOR CLUTTER REMOVAL THROUGH PYRAM...

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Conference on Chaos/Nonlinear Dynamics: Methods and Commercialization

作者： RUDIN, L KOEPFLER, G NORDBY, F MOREL, JM COGNITECH INC SANTA MONICACA

ISBN: (纸本)0819412864

Recent work has proven the feasibility and utility of 2-Normal segmentation as an image analysis tool. This technique, and the algorithm on which it is based, have shown dramatic and promising results for a number of image processing problems, such as clutter suppression, texture segmentation, motion analysis and object tracking. These capacities will be useful for clutter suppression, target location and classification, platform motion compensation, target tracking, vehicle guidance, battlefield mapping and target damage assessment. These and all applications of 2-Normal segmentation could easily employ and integrate multi-sensor data and /or multi-scale image preprocessing for analysis in two dimensions, three dimensions, or time sequence.

关键词： Image segmentation Wavelets Image processing algorithms and systems Image analysis Image processing algorithm development Detection and tracking algorithms Motion analysis Nonlinear filtering Wavelet transforms

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Quantization of color histograms using GLA 3

Quantization of color histograms using GLA

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Conference on Electronic Imaging and Multimedia Technology III

作者： Yang, CC Yip, MK Chinese Univ Hong Kong Dept Syst Engn & Engn Management Shatin Hong Kong Peoples R China

ISBN: (纸本)0819447145

Color histogram has been used as one of the most important image descriptor in a wide range of content-based image retrieval (CBIR) projects for color image indexing. It captures the global chromatic distribution of an image. Traditionally, there are two major approaches to quantize the color space: (1) quantize each dimension of a color coordinate system uniformly to generate a fixed number of bins;and (2) quantize a color coordinate system arbitrarily. The first approach works best on cubical color coordinate systems, such as RGB. For other non-cubical color coordinate system, such as CIELAB and CIELUV, some bins may fall out of the gamut (transformed from the RGB cube) of the color space. As a result, it reduces the effectiveness of the color histogram and hence reduces the retrieval performance. The second approach uses arbitrarily quantization. The volume of the bins is not necessary uniform. As a result, it affects the effectiveness of the histogram significantly. In this paper, we propose to develop the color histogram by tessellating the non-cubical color gamut transformed from RGB cube using a vector quantization (VQ) method, the General Loyld algorithm (GLA) [6]. Using such approach, the problem of empty bins due to the gamut of the color coordinate system can be avoided. Besides, all bins quantized by GLA will occupy the same volume. It guarantees that uniformity of each quantized bins in the histogram. An experiment has been conducted to evaluate the quantitative performance of our approach. The image collection from UC Berkeley's digital library project is used as the test bed. The indexing effectiveness of a histogram space [3] is used as the measurement of the performance. The experimental result shows that using the GLA quantization approach significantly increase the indexing effectiveness.

关键词： Quantization RGB color model algorithm development Colorimetry Feature extraction Visualization Content based image retrieval Image retrieval Digital imaging Systems engineering

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Multi-resolution mesh representation for biomechanical agents

Multi-resolution mesh representation for biomechanical agent...

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5th International Workshop on Nondestructive Testing and Computer Simulations in Science and Engineering

作者： Grachev, PN Belyaev, SY Sholukha, VA St Petersburg State Tech Univ Appl Math Dept St Petersburg 195251 Russia

ISBN: (纸本)0819443662

The paper is dedicated to computer graphics problems that appear when visualizing virtual biomechanical agents in real time rendering. Visualization speed and quality directly depend on the LOD (level of detail) of an agent model. We discuss the problem of dynamic changes in geometric model LOD in real time. An algorithm is suggested that allows us to save computer resources significantly along with dynamic mesh representation and to speed up the model rendering in real time mode.

关键词： 3D modeling Visual process modeling Visualization Animal model studies Matrices Cameras Computer graphics algorithm development 3D applications Robots

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Application of UV-Raman spectroscopy to the detection of chemical and biological threats

Application of UV-Raman spectroscopy to the detection of che...

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Conference on Chemical and Biological Point Sensors for Homeland Defense

作者： Sedlacek, AJ Christesen, S Chyba, T Ponsardin, P Brookhaven Natl Lab Upton NY 11973 USA

ISBN: (纸本)0819451584

Brookhaven National Laboratory (BNL), Edgewood Chemical and Biological Center (ECBC) and ITT Industries Advanced Engineering and Sciences Division (AES) have been collaborating on the transitioning and subsequent development of a short-range, non-contact Raman lidar system specifically designed to detect and identify chemical agents on the battlefield. [The instrument, referred to as LISA (Laser Interrogation of Surface Agents), will the subject of an accompanying paper.] As part of this collaboration, BNL has the responsibility for developing a spectral database (library) of surrogates and precursors for use with LISA's pattern recognition algorithms. In this paper, the authors discuss the phenomenon of UV Raman and resonance-enhanced Raman spectroscopy, the development of an instrument-independent Raman spectral library, and highlight the exploitable characteristics present in the acquired spectral signatures that suggest potential utility in our country's efforts on Homeland Security.

关键词： Biological detection systems Raman spectroscopy algorithm development Industrial chemicals Nanoimprint lithography Spectroscopes Arsenic Databases Laser development LIDAR

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A Study of Malware Detection on Smart Mobile Devices

A Study of Malware Detection on Smart Mobile Devices

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Conference on Cyber Sensing

作者： Yu, Wei Zhang, Hanlin Xu, Guobin Towson Univ Dept Comp & Informat Sci Towson MD 21252 USA

ISBN: (纸本)9780819495488

The growing in use of smart mobile devices for everyday applications has stimulated the spread of mobile malware, especially on popular mobile platforms. As a consequence, malware detection becomes ever more critical in sustaining the mobile market and providing a better user experience. In this paper, we review the existing malware and detection schemes. Using real-world malware samples with known signatures, we evaluate four popular commercial anti-virus tools and our data shows that these tools can achieve high detection accuracy. To deal with the new malware with unknown signatures, we study the anomaly based detection using decision tree algorithm. We evaluate the effectiveness of our detection scheme using malware and legitimate software samples. Our data shows that the detection scheme using decision tree can achieve a detection rate up to 90% and a false positive rate as low as 10%.

关键词： Mobile devices Computer security Analytical research Information security Detection and tracking algorithms Cell phones Operating systems algorithm development Humidity Mobile communications

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